Changeset 3892 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis

Timestamp:

06/02/10 19:10:35 (15 years ago)

Author:

gkronber

Message:

Improved code for analyzers for SVR and symbolic regression. #1009

Location:

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.3

Files:

• LinearRegression.cs (modified) (5 diffs)
• SupportVectorMachine.cs (modified) (4 diffs)

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.3/LinearRegression.cs

@@ -120 +120 @@
 
     protected override void Problem_Reset(object sender, EventArgs e) {
-      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
-      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;      
+      UpdateAlgorithmParameterValues();
       base.Problem_Reset(sender, e);
     }
@@ -129 +128 @@
       solutionCreator.DataAnalysisProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name;
       evaluator.RegressionProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name;
-      analyzer.ProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name; 
-      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
-      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;
+      analyzer.ProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name;
+      UpdateAlgorithmParameterValues();
       Problem.Reset += new EventHandler(Problem_Reset);
       base.OnProblemChanged();
     }
+
 
     #endregion
@@ -145 +144 @@
       solutionCreator.SymbolicExpressionTreeParameter.ActualName = LinearRegressionModelParameterName;
 
-      evaluator.LowerEstimationLimitParameter.Value = new DoubleValue(double.NegativeInfinity);
-      evaluator.UpperEstimationLimitParameter.Value = new DoubleValue(double.PositiveInfinity);
       evaluator.SymbolicExpressionTreeParameter.ActualName = solutionCreator.SymbolicExpressionTreeParameter.ActualName;
       evaluator.SymbolicExpressionTreeInterpreterParameter.ActualName = ModelInterpreterParameter.Name;
@@ -161 +158 @@
       analyzer.QualityParameter.Depth = 0;
       analyzer.SymbolicExpressionTreeInterpreterParameter.ActualName = ModelInterpreterParameter.Name;
-      analyzer.LowerEstimationLimitParameter.Value = new DoubleValue(double.NegativeInfinity);
-      analyzer.UpperEstimationLimitParameter.Value = new DoubleValue(double.PositiveInfinity);
 
       if (Problem != null) {
@@ -171 +166 @@
       }
     }
+
+    private void UpdateAlgorithmParameterValues() {
+      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
+      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;
+      //var targetValues =
+      //  Problem.DataAnalysisProblemData.Dataset.GetVariableValues(Problem.DataAnalysisProblemData.TargetVariable.Value,
+      //  TrainingSamplesStartParameter.Value.Value, TrainingSamplesEndParameter.Value.Value);
+      //double range = targetValues.Max() - targetValues.Min();
+      //double lowerEstimationLimit = targetValues.Average() - 10.0 * range;
+      //double upperEstimationLimit = targetValues.Average() + 10.0 * range;
+      //evaluator.LowerEstimationLimitParameter.Value = new DoubleValue(lowerEstimationLimit);
+      //evaluator.UpperEstimationLimitParameter.Value = new DoubleValue(upperEstimationLimit);
+      //analyzer.LowerEstimationLimitParameter.Value = new DoubleValue(lowerEstimationLimit);
+      //analyzer.UpperEstimationLimitParameter.Value = new DoubleValue(upperEstimationLimit);
+    }
     #endregion
   }

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.3/SupportVectorMachine.cs

@@ -169 +169 @@
 
     protected override void Problem_Reset(object sender, EventArgs e) {
-      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
-      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;
+      UpdateAlgorithmParameters();
       base.Problem_Reset(sender, e);
     }
@@ -179 +178 @@
       evaluator.DataAnalysisProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name;
       analyzer.ProblemDataParameter.ActualName = Problem.DataAnalysisProblemDataParameter.Name;
-      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
-      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;
+      UpdateAlgorithmParameters();
       Problem.Reset += new EventHandler(Problem_Reset);
       base.OnProblemChanged();
@@ -210 +208 @@
       analyzer.QualityParameter.ActualName = mseEvaluator.MeanSquaredErrorParameter.ActualName;
       analyzer.QualityParameter.Depth = 0;
-      analyzer.LowerEstimationLimitParameter.Value = new DoubleValue(double.NegativeInfinity);
-      analyzer.UpperEstimationLimitParameter.Value = new DoubleValue(double.PositiveInfinity);
 
       if (Problem != null) {
@@ -220 +216 @@
       }
     }
+
+    private void UpdateAlgorithmParameters() {
+      TrainingSamplesStartParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesStart;
+      TrainingSamplesEndParameter.ActualValue = Problem.DataAnalysisProblemData.TrainingSamplesEnd;
+    }
     #endregion
   }